Fluvial Architecture Knowledge Transfer System (FAKTS): querying the database from the FRG website

Luca Colombera, Nigel P. Mountney, Marco Patacci Fluvial & Eolian Research Group – University of Leeds

Querying FAKTS

Two alternative ways to interrogate FAKTS

: -

WEB-BASED FRONT-END

hosted on FRG website. Easy to use, but of limited capability. Queries can be run on the website without requiring download of software or data.

-

SQL QUERIES

on MySQL.

More difficult to use, but it enables full database interrogation.

Queries are run locally, requiring download of software (MySQL and HeidiSQL) and database.

Web-accessible front end

Easy to use, limited capability of query

: - depositional and architectural elements currently included; - dimension and transition data made available; - limited number of filters.

Further developments will follow.

Web-accessible front end Go to:

http://frg.leeds.ac.uk/

Web-accessible front end Log in to

‘Sponsors’ Pages’

Web-accessible front end Select

‘FAKTS Database’

from left-hand panel

Web-accessible front end Excel spreadsheets containing example output retrieved from the fully-searchable version of FAKTS are available for download.

Web-accessible front end Excel spreadsheets containing example output retrieved from the fully-searchable version of FAKTS are available for download.

Web-accessible front end Excel spreadsheets containing example output retrieved from the fully-searchable version of FAKTS are available for download.

Web-accessible front end The menu-driven front-end can be accessed from the same page.

Web-accessible front end Queries can be formulated and run from this page.

Web-accessible front end (1) the scale of observation (scale of genetic unit) should be chosen from the right-hand panel.

Web-accessible front end Let’s say we are interested in large-scale depositional elements.

Web-accessible front end The number in brackets under the genetic-unit type tells us that 46 studies contain information at the depositional-element scale.

Web-accessible front end (2) the type of output (i.e. geometry or transition data) we are interested in should be selected next.

Web-accessible front end Let’s say we are interested in obtaining dimensional parameters.

Web-accessible front end Now we can filter the database on the parameters on which the depositional systems are classified (lower right-hand panel).

Web-accessible front end (3) Let’s say we are interested only in data from convergent tectonic settings.

Web-accessible front end (3) let’s say we are interested only in data from convergent tectonic settings: we get 22 case studies now.

Web-accessible front end (4) now, we want to further filter the database by selecting only systems from subhumid basins.

Web-accessible front end (4) now, we want to further filter the database by selecting only systems from subhumid basins.

Web-accessible front end 11 case studies are now left.

Web-accessible front end 11 case studies are now left: here you see them listed.

Web-accessible front end (5) let’s say that we want to exclude modern-river data from the South Saskatchewan: just click on (Remove) in its box.

Web-accessible front end The South Saskatchewan data has now been removed.

Web-accessible front end A summary of the filters applied and case studies considered is presented at the top of the central panel.

Web-accessible front end (6) now we can select the type of depositional element (channel complex or floodplain) for which we want dimensional data.

Web-accessible front end (6) now we can select the type of depositional element (channel complex or floodplain) for which we want dimensional data.

Web-accessible front end (7) now we only need to click on ‘download’ to obtain the Excel spreadsheet with the filtered channel-complex output.

Web-accessible front end The Excel spreadsheet with FAKTS output can now be opened or downloaded for analysis of channel-complex geometries.

Web-accessible front end The Excel spreadsheet contains both architectural data, listed separately for each individual channel complex, and metadata.

Web-accessible front end If we want to run a new query, we can reset the filters applied by clicking on ‘Reset Filters’, at the top of the right-hand panel.

Web-accessible front end The screen will appear as above, as a confirmation that the filters have been reset.

Web-accessible front end Let’s see another example: we want to derive lateral transitions statistics of CH architectural elements in braided systems.

Web-accessible front end (1) therefore we select the scale of genetic unit of interest, which is now ‘Architectural Elements’.

Web-accessible front end Now we need to select again the type of output: unit transitions.

Web-accessible front end (2) we therefore click on ‘Unit Transitions’.

Web-accessible front end Now we want to filter the database on river pattern, so that only braided systems are included in the query.

Web-accessible front end (3) we therefore click on ‘Braided’ under the ‘River Pattern’ filter.

Web-accessible front end Now, let’s say we only want to derive output from the highest quality case studies: we can filter on case

data quality index

.

Web-accessible front end (4) we therefore click on ‘A’ under the ‘Dataset DQI’ filter.

Web-accessible front end (5) now we can select the direction of transition in which we are interested from the drop-down menu in the central panel.

Web-accessible front end (5) finally, we need to select the type of architectural element for which we want to derive transition statistics.

Web-accessible front end (6) now, we can download the Excel spreadsheet with the relevant output by clicking on ‘Down. Excel’.

Web-accessible front end The Excel spreadsheet with FAKTS output can now be opened or downloaded for analysis of CH lateral-transition data.

Web-accessible front end Again, the Excel spreadsheet contains the raw architectural data, each row represents a lateral transition to an individual element.

Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies.

Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies.

Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies.

Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies.

Web-accessible front end From these data, information can be derived in the form of transition counts, with which to obtain transition frequencies.

Conclusions

FAKTS interrogation MySQL queries

- HeidiSQL front-end requires basic SQL knowledge; - output referring to any type of genetic unit can be generated; - any type of output can be queried (including proportions, grain size, etc.); - all available filters can be applied; - it is possible to tailor the query so that output does not require further data analysis.

FRG website

- user-friendly menu-driven front end; - depositional and architectural elements currently included; - dimension and transition data currently made available; - limited number of filters; - output is given in the form of raw data, which may require further analysis.

Further developments will follow.